Unmanned Vehicle Data Processing via Computing Intermediary
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Solution Overview
Problem
Current unmanned vehicle systems lack efficient methods for processing and utilizing data captured during operations, particularly in remote environments like oilfields, which limits their ability to perform complex tasks and make informed decisions.
Innovation Solution
Integration of unmanned vehicles with computing devices for data processing, storage, and communication, enabling real-time data analysis and integration with application programs like Petrel and Ocean, allowing for automated tasks, data sharing, and decision-making through sensing devices such as cameras, location sensors, and electromagnetic spectrum sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If unmanned vehicles are deployed to remote environments for data collection, then the ability to perform exploration and monitoring tasks is improved, but the efficiency of processing and utilizing captured data deteriorates
Solution Approach 1:
A computing device acts as an intermediary between the UV and the user/external systems. The computing device receives sensed data from the UV, processes it, and generates useful information or control signals, thereby resolving the data processing inefficiency while maintaining the UV's versatility in remote operations
Solution Approach 2:
The system is segmented into distinct functional components: the UV for data collection in remote environments, and a separate computing device for data processing. This segmentation allows each component to be optimized independently - the UV for adaptability in field operations and the computing device for processing efficiency
2Quantity of substance
If more sensing devices are integrated on UVs to capture diverse data, then the quantity and variety of captured data is improved, but the complexity of processing and managing this data increases
Solution Approach 1:
The computing device is designed as a universal processing platform that can handle multiple types of sensed data from various sensing devices (cameras, electromagnetic spectrum sensors, etc.). It provides multi-functional capabilities including data processing, storage, and integration with application programs, thereby managing diverse data without proportionally increasing complexity
Solution Approach 2:
The computing device serves as an intermediary that consolidates and manages data from multiple sensing devices. Instead of requiring complex processing at the UV level, the computing device centralizes data management functions, reducing the complexity burden on the UV system while handling diverse data types
3Object-affected harmful factors
If UVs operate autonomously in remote areas without human presence, then human risk is reduced, but the capability for real-time data analysis and decision-making deteriorates
Solution Approach 1:
The UV system provides self-service capabilities through autonomous operation and integrated computing functionality. The computing device processes data in real-time and can generate control signals to autonomously adjust UV operations, enabling real-time decision-making without human intervention while maintaining safety
Solution Approach 2:
The system implements feedback loops where the computing device processes sensed data in real-time and generates control signals that are sent back to the UV to adjust its operation. This closed-loop feedback enables autonomous real-time decision-making, compensating for the absence of human operators while maintaining operational effectiveness
Data Source
AI summary
The present invention is directed to unmanned vehicle (UV) systems and methods. A method may include capturing data with at least one UV proximate an area of interest. The method may also include processing the data at a computing device. In addition, the method may include at least storing the processed data, sharing the processed data with another device, combining the processed data with related historical data, developing a model based at least partially on the processed data, determining at least one future task to be performed by the UV based at least partially on the processed data, or any combination thereof.